Weighting Factor Design in Model Predictive Control for Power Converters

Perez-Guzman, Ricardo Enrique; Rivera, Marco; Wheeler, Patrick W.

Abstract

Model-based predictive control is an important multi-objective control strategy in power converters, but it must be properly designed. This research shows different alternatives to improve the cost function in model-based predictive control. For this purpose, the procedure for adjusting the weight factors in the cost functions, all relevant elements and some examples that demonstrate the influence of each term in the equation is presented. The cost functions are characterized and simulated to verify the effectiveness of the working method and the claims made in this investigation. It was found that modelbased predictive control is a powerful alternative when there are multiple objectives, which can be included efficiently within a cost function. However, it is necessary to investigate the ideal value of each of these terms.

Citation

Perez-Guzman, R. E., Rivera, M., & Wheeler, P. W. (2019). Weighting Factor Design in Model Predictive Control for Power Converters. In IEEE Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies. https://doi.org/10.1109/CHILECON47746.2019.8988109

• Conference Name: 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)
• Conference Location: Valparaiso, Chile
• Start Date: Nov 13, 2019
• End Date: Nov 27, 2019
• Acceptance Date: Sep 8, 2019
• Online Publication Date: Feb 10, 2020
• Publication Date: 2019-11
• Deposit Date: Mar 26, 2020
• Publicly Available Date: Mar 27, 2020
• Book Title: IEEE Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies
• ISBN: 9781728131856
• DOI: https://doi.org/10.1109/CHILECON47746.2019.8988109
• Keywords: Predictive control , Cost function , Weighting factor
• Public URL: https://nottingham-repository.worktribe.com/output/4205729
• Publisher URL: https://ieeexplore.ieee.org/document/8988109
• Additional Information: © 2020 IEEE.Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.